class_docstr: Linearly spaced clipping.
  
  `n_samples` are generated with clipping spaced linearly
  between `lower` and `upper`.
  
  This transformation affects the following attributes:
  - Audio
  
  Attributes
  ----------
  n_samples : int > 0
      Number of deformations to generate
  
  lower : float > 0.0
  upper : float in (lower, 1.0)
      Minimum and maximum bounds on the clip parameters
  
  See Also
  --------
  Clipping
  RandomClipping
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code: def states(self, jam):
      clip_limits = np.linspace(
          self.lower, self.upper, num=self.n_samples, endpoint=True
      )
  
      for clip_limit in clip_limits:
          yield dict(clip_limit=clip_limit)
  
file_path: muda/muda/deformers/clipping.py
imports: import numpy
  from ..base import BaseTransformer, _get_rng
label_desc: Use image node_id 2 for calling the LinearClipping obj's underlying member method code with example usage: obj.states(jam) without return types